Experimental Evaluation of a LoRa Wildlife Monitoring Network in a Forest Vegetation Area

Smart agriculture and wildlife monitoring are one of the recent trends of Internet of Things (IoT) applications, which are evolving in providing sustainable solutions from producers. This article details the design, development and assessment of a wildlife monitoring application for IoT animal repelling devices that is able to cover large areas, thanks to the low power wide area networks (LPWAN), which bridge the gap between cellular technologies and short range wireless technologies. LoRa, the global de-facto LPWAN, continues to attract attention given its open specification and ready availability of off-the-shelf hardware, with claims of several kilometers of range in harsh challenging environments. At first, this article presents a survey of the LPWAN for smart agriculture applications. We proceed to evaluate the performance of LoRa transmission technology operating in the 433 MHz and 868 MHz bands, aimed at wildlife monitoring in a forest vegetation area. To characterize the communication link, we mainly use the signal-to-noise ratio (SNR), received signal strength indicator (RSSI) and packet delivery ratio (PDR). Findings from this study show that achievable performance can greatly vary between the 433 MHz and 868 MHz bands, and prompt caution is required when taking numbers at face value, as this can have implications for IoT applications. In addition, our results show that the link reaches up to 860 m in the highly dense forest vegetation environment, while in the not so dense forest vegetation environment, it reaches up to 2050 m

Performance Analysis of a DEKF for Available Bandwidth Measurement

The paper presents a characterisation analysis of a measurement algorithm based on a Discrete-time Extended Kalman Filter (DEKF), which has recently been proposed for the estimation and tracking of end-to-end available bandwidth. The analysis is carried out by means of simulations for different rates of variations of the available bandwidth and permits assessing the performance of the measurement algorithm for different values of the filter parameters, that is, the covariance matrixes of the measurement and process noise

Internet of Things and Intelligent Technologies for Efficient Energy Management in a Smart Building Environment

Internet of Things (IoT) is attempting to transform modern buildings into energy efficient, smart, and connected buildings, by imparting capabilities such as real-time monitoring, situational awareness and intelligence, and intelligent control. Digitizing the modern day building environment using IoT improves asset visibility and generates energy savings. This dissertation provides a survey of the role, impact, and challenges and recommended solutions of IoT for smart buildings. It also presents an IoT-based solution to overcome the challenge of inefficient energy management in a smart building environment. The proposed solution consists of developing an Intelligent Computational Engine (ICE), composed of various IoT devices and technologies for efficient energy management in an IoT driven building environment. ICE’s capabilities viz. energy consumption prediction and optimized control of electric loads have been developed, deployed, and dispatched in the Real-Time Power and Intelligent Systems (RTPIS) laboratory, which serves as the IoT-driven building case study environment. Two energy consumption prediction models viz. exponential model and Elman recurrent neural network (RNN) model were developed and compared to determine the most accurate model for use in the development of ICE’s energy consumption prediction capability. ICE’s prediction model was developed in MATLAB using cellular computational network (CCN) technique, whereas the optimized control model was developed jointly in MATLAB and Metasys Building Automation System (BAS) using particle swarm optimization (PSO) algorithm and logic connector tool (LCT), respectively. It was demonstrated that the developed CCN-based energy consumption prediction model was highly accurate with low error % by comparing the predicted and the measured energy consumption data over a period of one week. The predicted energy consumption values generated from the CCN model served as a reference for the PSO algorithm to generate control parameters for the optimized control of the electric loads. The LCT model used these control parameters to regulate the electric loads to save energy (increase energy efficiency) without violating any operational constraints. Having ICE’s energy consumption prediction and optimized control of electric loads capabilities is extremely useful for efficient energy management as they ensure that sufficient energy is generated to meet the demands of the electric loads optimally at any time thereby reducing wasted energy due to excess generation. This, in turn, reduces carbon emissions and generates energy and cost savings. While the ICE was tested in a small case-study environment, it could be scaled to any smart building environment

Optimisation of a propagation model for last mile connectivity with low altitude platforms using machine learning

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonOur related research review on propagation models reveals six factors that are significant in last mile connectivity via LAP: path loss, elevation angle, LAP altitude, coverage area, power consumption, operation frequency, interference, and antenna type. These factors can help with monitoring system performance, network planning, coverage footprint, receivers’ line-of-sight, quality of service requirements, and data rates which may all vary in response to geomorphology characteristics. Several competing propagation models have been proposed over the years but whilst they collectively raise many shortcomings such as limited altitude up to few tens of meters, lack of cover across different environments, low perdition accuracy they also exhibit several advantages. Four propagation models, which are representatives of their types, have been selected since they exhibit advantages in relation to high altitude, wide coverage range, adaption across different terrains. In addition, all four have been extensively deployed in the past and as a result their correction factors have evolved over the years to yield extremely accurate results which makes the development and evaluation aspects of this research very precise. The four models are: ITU-R P.529-3, Okumura, Hata-Davidson, and ATG. The aim of this doctoral research is to design a new propagation model for last-mile connectivity using LAPs technology as an alternative to aerial base station that includes all six factors but does not exhibit any of the shortcomings of existing models. The new propagation model evolves from existing models using machine learning. The four models are first adapted to include the elevation angle alongside the multiple-input multiple-output diversity gain, our first novelty in propagation modelling. The four adapted models are then used as input in a Neural Network framework and their parameters are clustered in a Self-Organizing-Map using a minimax technique. The framework evolves an optimal propagation model that represents the main research contribution of this research. The optimal propagation model is deployed in two proof-of-concept applications, a wireless sensor network, and a cellular structure. The performance of the optimal model is evaluated and then validated against that of the four adapted models first in relation to predictions reported in the literature and then in the context of the two proof-of-concept applications. The predictions of the optimised model are significantly improved in comparison to those of the four adapted propagation models. Each of the two proof-of-concept applications also represent a research novelty.The Royal Saudi Embassy and the Saudi Cultural Bureau in London, and Taif University in the Kingdom of Saudi Arabia

Ultra Low Power Communication Protocols for UWB Impulse Radio Wireless Sensor Networks

This thesis evaluates the potential of Ultra Wideband Impulse Radio for wireless sensor network applications. Wireless sensor networks are collections of small electronic devices composed of one or more sensors to acquire information on their environment, an energy source (typically a battery), a microcontroller to control the measurements, process the information and communicate with its peers, and a radio transceiver to enable these communications. They are used to regularly collect information within their deployment area, often for very long periods of time (up to several years). The large number of devices often considered, as well as the long deployment durations, makes any manual intervention complex and costly. Therefore, these networks must self-configure, and automatically adapt to changes in their electromagnetic environment (channel variations, interferers) and network topology modifications: some nodes may run out of energy, or suffer from a hardware failure. Ultra Wideband Impulse Radio is a novel wireless technology that, thanks to its extremely large bandwidth, is more robust to frequency dependent propagation effects. Its impulsional nature makes it robust to multipath fading, as the short duration of the pulses leads most multipath components to arrive isolated. This technology should also enable high precision ranging through time of flight measurements, and operate at ultra low power levels. The main challenge is to design a system that reaches the same or higher degree of energy savings as existing narrowband systems considering all the protocol layers. As these radios are not yet widely available, the first part of this thesis presents Maximum Pulse Amplitude Estimation, a novel approach to symbol-level modeling of UWB-IR systems that enabled us to implement the first network simulator of devices compatible with the UWB physical layer of the IEEE 802.15.4A standard for wireless sensor networks. In the second part of this thesis, WideMac, a novel ultra low power MAC protocol specifically designed for UWB-IR devices is presented. It uses asynchronous duty cycling of the radio transceiver to minimize the power consumption, combined with periodic beacon emissions so that devices can learn each other's wake-up patterns and exchange packets. After an analytical study of the protocol, the network simulation tool presented in the first part of the thesis is used to evaluate the performance of WideMac in a medical body area network application. It is compared to two narrowband and an FM-UWB solutions. The protocol stack parameters are optimized for each solution, and it is observed that WideMac combined to UWB-IR is a credible technology for such applications. Similar simulations, considering this time a static multi-hop network are performed. It is found that WideMac and UWB-IR perform as well as a mature and highly optimized narrowband solution (based on the WiseMAC ULP MAC protocol), despite the lack of clear channel assessment functionality on the UWB radio. The last part of this thesis studies analytically a dual mode MAC protocol named WideMac-High Availability. It combines the Ultra Low PowerWideMac with the higher performance Aloha protocol, so that ultra low power consumption and hence long deployment times can be combined with high performance low latency communications when required by the application. The potential of this scheme is quantified, and it is proposed to adapt it to narrowband radio transceivers by combining WiseMAC and CSMA under the name WiseMAC-HA

Telecommunications Networks

This book guides readers through the basics of rapidly emerging networks to more advanced concepts and future expectations of Telecommunications Networks. It identifies and examines the most pressing research issues in Telecommunications and it contains chapters written by leading researchers, academics and industry professionals. Telecommunications Networks - Current Status and Future Trends covers surveys of recent publications that investigate key areas of interest such as: IMS, eTOM, 3G/4G, optimization problems, modeling, simulation, quality of service, etc. This book, that is suitable for both PhD and master students, is organized into six sections: New Generation Networks, Quality of Services, Sensor Networks, Telecommunications, Traffic Engineering and Routing

Exploring the challenges and opportunities of image processing and sensor fusion in autonomous vehicles: A comprehensive review

Autonomous vehicles are at the forefront of future transportation solutions, but their success hinges on reliable perception. This review paper surveys image processing and sensor fusion techniques vital for ensuring vehicle safety and efficiency. The paper focuses on object detection, recognition, tracking, and scene comprehension via computer vision and machine learning methodologies. In addition, the paper explores challenges within the field, such as robustness in adverse weather conditions, the demand for real-time processing, and the integration of complex sensor data. Furthermore, we examine localization techniques specific to autonomous vehicles. The results show that while substantial progress has been made in each subfield, there are persistent limitations. These include a shortage of comprehensive large-scale testing, the absence of diverse and robust datasets, and occasional inaccuracies in certain studies. These issues impede the seamless deployment of this technology in real-world scenarios. This comprehensive literature review contributes to a deeper understanding of the current state and future directions of image processing and sensor fusion in autonomous vehicles, aiding researchers and practitioners in advancing the development of reliable autonomous driving systems

Intelligent Network Infrastructures: New Functional Perspectives on Leveraging Future Internet Services

The Internet experience of the 21st century is by far very different from that of the early '80s. The Internet has adapted itself to become what it really is today, a very successful business platform of global scale. As every highly successful technology, the Internet has suffered from a natural process of ossification. Over the last 30 years, the technical solutions adopted to leverage emerging applications can be divided in two categories. First, the addition of new functionalities either patching existing protocols or adding new upper layers. Second, accommodating traffic grow with higher bandwidth links. Unfortunately, this approach is not suitable to provide the proper ground for a wide gamma of new applications. To be deployed, these future Internet applications require from the network layer advanced capabilities that the TCP/IP stack and its derived protocols can not provide by design in a robust, scalable fashion. NGNs (Next Generation Networks) on top of intelligent telecommunication infrastructures are being envisioned to support future Internet Services. This thesis contributes with three proposals to achieve this ambitious goal. The first proposal presents a preliminary architecture to allow NGNs to seamlessly request advanced services from layer 1 transport networks, such as QoS guaranteed point-to-multipoint circuits. This architecture is based on virtualization techniques applied to layer 1 networks, and hides from NGNs all complexities of interdomain provisioning. Moreover, the economic aspects involved were also considered, making the architecture attractive to carriers. The second contribution regards a framework to develop DiffServ-MPLS capable networks based exclusively on open source software and commodity PCs. The developed DiffServ-MPLS flexible software router was designed to allow NGN prototyping, that make use of pseudo virtual circuits and assured QoS as a starting point of development. The third proposal presents a state of the art routing and wavelength assignment algorithm for photonic networks. This algorithm considers physical layer impairments to 100% guarantee the requested QoS profile, even in case of single network failures. A number of novel techniques were applied to offer lower blocking probability when compared with recent proposed algorithms, without impacting on setup delay time